Remote sensing technologies supporting rockfall hazard assessment for transportation routes management

Abstract

Remote sensing technologies offer enhanced capabilities for the assessment of rockfall hazard impacting transportation networks and the related risk management. This study examines the application of UA V-based photogrammetry and terrestrial laser scanning (TLS) for comprehensive geomechanical characterisation of rock masses, as well as the potential of photomonitoring techniques for slope stability assessment. A rock cliff located between the towns of Minori and Maiori (SA , Italy) was selected as the test site. Photogrammetric surveys were conducted using DJI Mavic 3 and DJI Matrice 200 aerial platforms. The surveys were performed at two flight distances (15 and 35 meters) for a portion of the rock face to investigate the effect of camerato-subject range on the resulting point cloud properties. The derived point clouds were analysed to extract geostructural and geomechanical parameters, including discontinuity orientation, normal spacing, Jv, RQD, and block volumes. Semi-automatic analyses demonstrated the viability of both photogrammetric and TLS approaches, while highlighting the need for methodological adaptations in the photogrammetric method due to reconstruction challenges posed by the installed protective rockfall net. Additionally, the study explored the use of photomonitoring for change detection of natural slopes, highlighting its potential as a complementary technique. The integration of multiple remote sensing methods provides a robust framework for slope stability assessment and management, contributing to enhanced transportation infrastructure resilience.